A New Intelligent Approach for Mobile Robot Navigation

  • Prases Kumar Mohanty
  • Dayal R. Parhi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8251)


In recent times computational intelligent techniques such as fuzzy inference system (FIS), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are mainly considered as effective and suitable optimization methods for modeling an engineering system. In this paper an efficient hybrid technique has been applied for mobile robot navigation using multiple adaptive neuro-fuzzy inference system (MANFIS). ANFIS has taken the advantages of both fuzzy inference system and artificial neural network. First, we design an adaptive fuzzy controller with four input parameters, two types of output parameters and three parameters each. Next each adaptive fuzzy controller acts as a single Sugeno-Takagi type fuzzy inference system where inputs are the different sensor based information and output corresponds to the velocity of the mobile robot. The implementation of the proposed navigational controller is discussed via numerous simulation examples. It is found that such an adaptive neuro-fuzzy controller is successfully and quickly finding targets in an unknown or partially unknown environment.


Mobile robot Navigation Neuro-fuzzy Obstacle avoidance 


  1. 1.
    Latombe, J.C.: Robot Motion Planning. Kluwer Academic Publishers, New York (1990)Google Scholar
  2. 2.
    Canny, J.E.: The Complexity of Robot Motion Planning. MIT Press, Cambridge (1988)Google Scholar
  3. 3.
    Lozano-Perez, T.: A simple motion planning algorithm for general robot manipulators. IEEE Journal of Robotics and Automation 3, 224–238 (1987)CrossRefGoogle Scholar
  4. 4.
    Leven, D., Sharir, M.: Planning a purely translational motion for a convex object in two dimensional space using generalized voronoi diagrams. Discrete & Computational Geometry 2, 9–31 (1987)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Payton, D., Rosenblatt, J., Keirsey, D.: Grid- based mapping for autonomous mobile robot. Robotics and Autonomous Systems 11, 13–21 (1993)CrossRefGoogle Scholar
  6. 6.
    Regli, L.: Robot Lab: Robot Path Planning. Lectures Notes of Department of Computer Science. Drexel University (2007)Google Scholar
  7. 7.
    Khatib, O.: Real time Obstacle Avoidance for manipulators and Mobile Robots. In: IEEE Conference on Robotics and Automation, vol. 2, p. 505 (1985)Google Scholar
  8. 8.
    Fujimura, K.: Motion Planning in Neritic Environments. Springer (1991)Google Scholar
  9. 9.
    Ibrahim, M.Y., Fernandes, A.: Study on Mobile Robot Navigation Techniques. In: IEEE International Conference on Industrial Technology, December 8-10, vol. 1, pp. 230–236 (2004)Google Scholar
  10. 10.
    Huq, R., Mann, G.K.I., Gosine, R.G.: Mobile robot navigation using motor schema and fuzzy content behavior modulation. Application of Soft Computing 8, 422–436 (2008)CrossRefGoogle Scholar
  11. 11.
    Selekwa, M.F., Dunlap, D.D., Shi, D., Collins Jr., E.G.: Robot navigation in very cluttered environment by preference based fuzzy behaviors. Autonomous System 56, 231–246 (2007)CrossRefGoogle Scholar
  12. 12.
    Abdessemed, F., Benmahammed, K., Monacelli, E.: A fuzzy based reactive controller for a non-holonomic mobile robot. Robotics Autonomous System 47, 31–46 (2004)CrossRefGoogle Scholar
  13. 13.
    Pradhan, S.K., Parhi, D.R., Panda, A.K.: Fuzzy logic techniques for navigation of several mobile robots. Application of Soft Computing 9, 290–304 (2009)CrossRefGoogle Scholar
  14. 14.
    Motlagh, O., Tang, S.H., Ismail, N.: Development of a new minimum avoidance system for behavior based mobile robot. Fuzzy Sets System 160, 1929–1946 (2009)CrossRefGoogle Scholar
  15. 15.
    Velagic, J., Osmic, N., Lacevic, B.: Neural Network Controller for Mobile Robot Motion Control. World Academy of Science. Engineering and Technology 47, 193–198 (2008)Google Scholar
  16. 16.
    Singh, M.K., Parhi, D.R.: Intelligent Neuro-Controller for Navigation of Mobile Robot. In: Proceedings of the International Conference on Advances in Computing, Communication and Control, Mumbai, Maharashtra, India, pp. 123–128 (2009)Google Scholar
  17. 17.
    Castro, V., Neira, J.P., Rueda, C.L., Villamizar, J.C., Angel, L.: Autonomous Navigation Strategies for Mobile Robots using a Probabilistic Neural Network (PNN). In: 33rd Annual Conference of the IEEE Industrial Electronics Society, Taipei, Taiwan, pp. 2795–2800 (2007)Google Scholar
  18. 18.
    Yang, S.X., Meng, M.: An efficient neural network approach to dynamic robot motion planning. Neural Network 13, 143–148 (2000)CrossRefGoogle Scholar
  19. 19.
    Jang, J.S.R.: ANFIS: Adaptive network-based fuzzy inference system. IEEE Transaction on System, Man and Cybernetics Part B 23, 665–685 (1993)CrossRefGoogle Scholar
  20. 20.
    Song, K.T., Sheen, L.H.: Heuristic fuzzy-neuro network and its application to reactive navigation of a mobile robot. Fuzzy Sets Syst. 110, 331–340 (2000)CrossRefGoogle Scholar
  21. 21.
    Li, W., Ma, C., Wahl, F.M.: A neuro-fuzzy system architecture for behavior based control of a mobile robot in unknown environments. Fuzzy Sets Syst. 87, 133–140 (1997)CrossRefGoogle Scholar
  22. 22.
    Pradhan, S.K., Parhi, D.R., Panda, A.K.: Neuro-fuzzy technique for navigation of multiple mobile robots. Fuzzy Optimum Decision Making 5, 255–288 (2006)CrossRefzbMATHGoogle Scholar
  23. 23.
    Nefti, S., Oussalah, M., Djouani, K., Pontnau, J.: Intelligent Adaptive Mobile Robot Navigation. Journal of Intelligent and Robotic Systems 30, 311–329 (2001)CrossRefzbMATHGoogle Scholar
  24. 24.
    Ng, K.C., Trivedi, M.M.: A Neuro-Fuzzy Controller for Mobile Robot Navigation and Multi robot Convoying. IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics 28, 829–840 (1998)CrossRefGoogle Scholar
  25. 25.
    Hui, N.B., Mahendar, V., Pratihar, D.K.: Time-optimal, collision-free navigation of a car-like mobile robot using neuro-fuzzy approaches. Fuzzy Sets and Systems 157, 2171–2204 (2008)MathSciNetCrossRefGoogle Scholar
  26. 26.
    Godjevac, J., Steele, N.: Neuro-fuzzy control of a mobile robot. Neuro-Computing 28, 127–142 (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Prases Kumar Mohanty
    • 1
  • Dayal R. Parhi
    • 1
  1. 1.Robotics LaboratoryNational Institute of TechnologyRourkelaIndia

Personalised recommendations